Universität Wien
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040294 UK Econometrics and Causal Inference (BA) (2018W)

8.00 ECTS (4.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 03.10. 16:45 - 20:00 Hörsaal 3 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 10.10. 16:45 - 20:00 Studierzone
  • Wednesday 17.10. 16:45 - 20:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Thursday 18.10. 15:00 - 18:15 Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
  • Wednesday 07.11. 16:45 - 20:00 Studierzone
  • Wednesday 14.11. 16:45 - 20:00 Studierzone
  • Wednesday 21.11. 16:45 - 20:00 Studierzone
  • Friday 23.11. 13:15 - 16:30 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Wednesday 28.11. 16:45 - 20:00 Studierzone
  • Wednesday 05.12. 16:45 - 20:00 Studierzone
  • Wednesday 12.12. 16:45 - 20:00 Studierzone
  • Wednesday 09.01. 16:45 - 20:00 Studierzone
  • Wednesday 16.01. 16:45 - 20:00 Studierzone
  • Wednesday 23.01. 16:45 - 20:00 Studierzone
  • Wednesday 30.01. 16:45 - 20:00 Studierzone

Information

Aims, contents and method of the course

The aim of this course is to help you to understand modern applied econometric methods and to foster the skills needed to plan and execute your own empirical projects. Topics include randomized trials, regression, differences-in-differences, instrumental variables and regression-discontinuity designs. This is an “applied-empirical” course, meaning that priority will be given to concrete applications rather than to formal derivation of the econometrics methods used in the applications.

Assessment and permitted materials

Exam: 34%. Homework 33%. Presentation in class 33%.

Minimum requirements and assessment criteria

Assessment is based on one open-book exam, homework and a presentation in class.

Examination topics

All the material covered in class will be relevant for the exams.

Reading list

J. Angrist and J.S. Pischke, Mastering ‘Metrics: The Path from Cause to Effect, Princeton
University Press, 2014. http://masteringmetrics.com/

Association in the course directory

Last modified: Mo 07.09.2020 15:29